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7th Asian Conference on Artificial Intelligence technology, ACAIT 2023

作者： Zhou, Runlin Huang, Peiliang Zhang, Dingwen Ren, Jun Anhui University AHU-IAI Ai Joint Laboratory Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Northwestern Polytechnical University School of Automation Xi'an China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9798350359145

Low-light image enhancement (LLIE) is an important task in computer vision, aiming to improve the visual perception or interpretability of images captured in poorly illuminated environments. Recently, deep learning based methods have been extensively explored to address this issue. While many of these methods have achieved significant advancements in various evaluation metrics for LLIE, only a few have made progress in improving inference speed for the resulting images. As a result, achieving both high-quality enhancements and efficient inference speed remains a challenge. To tackle this challenge, we propose SeqEnhance, a fast LLIE method based on a predefined parameterized image processing pipeline. Our approach combines the inference capabilities of deep neural networks for parameter estimation and the efficient processing capabilities of image processing pipelines to generate enhanced images in an end-to-end manner. The experimental results demonstrate that the proposed method achieves competitive performance on image quality evaluation metrics such as PSNR and SSIM with a fast inference speed. © 2023 IEEE.

关键词： Image enhancement

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Flexible Physical Camouflage Generation Based on a Differential Approach

arXiv

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arXiv 2024年

作者： Li, Yang Tan, Wenyi Wang, Tingrui Liang, Xinkai Pan, Quan School of Automation Northwestern Polytechnical University Xi’an710072 China Laboratory of Science and Technology on Complex System Control and Intelligent Agent Cooperation Beijing China

To achieve attacks on object detection in the physical world, many existing studies focus on adversarial camouflage generation techniques, which involve applying adversarial textures onto the surface of the target. However, the neural renderers used in previous works cannot realistically simulate the physical world, and most texture rendering processes are implemented on 2D images, without fully considering the influence of the structural information of 3D models on texture overlay. To address these challenges, we introduce a novel neural rendering approach specifically tailored for adversarial camouflage within a versatile 3D rendering framework. Our method, named Flexible Physical-camouflage Attack (FPA), goes beyond traditional techniques by faithfully simulating lighting conditions, material variations of the camouflage, the angle and distance between the target and the camera, ensuring a nuanced and realistic representation of textures on a 3D target. To achieve this, we employ a generative approach that learns adversarial patterns from a diffusion model. This involves combining specially designed adversarial loss, smoothness loss, non-printable score loss, and concealment constraint loss to ensure the adversarial, printability, and concealable nature of camouflage in the physical world. Furthermore, we showcase the effectiveness of the proposed camouflage in sticker mode, demonstrating its ability to cover the target without compromising adversarial information. Through empirical and physical experiments, FPA exhibits strong performance in terms of attack success rate and transferability. Additionally, the designed sticker-mode camouflage, coupled with a concealment constraint, adapts to the environment, yielding diverse styles of texture. Our findings highlight the versatility and efficacy of the FPA approach in adversarial camouflage applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Camouflage

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Improved RRT Autonomous Exploration Method Based on Hybrid Clustering Algorithm

Improved RRT Autonomous Exploration Method Based on Hybrid C...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Yin, Yizhen Ma, Hongjun Liang, Xinkai College of Information Science and Engineering Northeastern University Liaoning Shenyang China Science and Technology On Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

In autonomous robot exploration, it is very important that the robot can autonomously plan the exploration path of the unknown environment and create a map representation of the surrounding environment. In the robot's autonomous environment traversal method, one branch is the frontier-based detection method. This method consumes more and more computing resources as the map expands and is not suitable for large-scale environment detection. Another branch is the random exploration method based on multiple rapidly-exploring randomized trees. This method uses the edge of the tree to search for the boundary, but the selection of the next exploration point is very demanding. This paper proposes an exploration point selection strategy based on the hybrid clustering method, which speeds up the RRT exploration method. Simulation experiments show that the improved RRT exploration method proposed in this paper takes less time to explore and build maps, especially in a large-scale mapping environment, which effectively improves the completeness and efficiency of mapping. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cluster analysis

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A Hierarchical Graph Search Method for Path Planning of Unmanned Ground Vehicle for Freight Transportation

A Hierarchical Graph Search Method for Path Planning of Unma...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Hu, Jianing Li, Zhen Guo, Sen Yao, Weiran School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China CRRC Nanjing Puzhen Co. Ltd. Nanjing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

For the problem of collision volume change when forklift unmanned vehicles work in complex storage environments, a multi-level graph search path planning method is proposed. The first level is the path planning of the Unmanned Ground Vehicle (UGV) body, which uses the grid map and the A* algorithm to plan the path of the UGV transferring in the scene;the second level is the joint path planning of the UGV and the object being carried, to avoid overcomplicating this issue, the unmanned vehicle will be limited to pushing the cargo only forwards. The third level is the path planning when the unmanned vehicle carries multiple objects, which decomposes the whole scene into multiple sub-scenes, plans the paths of the unmanned vehicle in the sub-scenes separately, and searches for the optimal combination of sub-scenes. Higher level searches will invoke lower level algorithms and provide a virtual scene and target as input. The experimental results show that this multilevel path planning method is optimal and complete in solving the forklift unmanned vehicle for handling a single object, and can give a feasible solution for handling multiple objects. © 2024 IEEE.

关键词： Ground vehicles

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Semi-autonomous Multicopter Formation control Under One Remote Pilot in GPS-Denied Environment

Semi-autonomous Multicopter Formation Control Under One Remo...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Gao, Yan Wei, Donghui Bai, Chenggang Quan, Quan School of Automation Science and Electrical Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

The multicopter formation is widely used in many different complex circumstances. And the semi-autonomous multicopter formation controlled with a single pilot on the ground draws people’s attention due to the great adaptability to various kinds of environments. In this paper, we focus on the problem of passing through narrow channels with semi-autonomous multicopter formation. Similar to the definition for a single multicopter, the altitude hold mode for the multicopter formation is defined first. Then, the formation decision-making and formation low-level control of the altitude hold mode are proposed one by one. Finally, a hardware-in-the-loop simulation and a real experiment are performed with four multicopters to pass through a narrow channel. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision making

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A dual-mode navigation algorithm based on Infrared and SAR information fusion

A dual-mode navigation algorithm based on Infrared and SAR i...

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2021 CIE International Conference on Radar, Radar 2021

作者： Yang, Yanjiao Qu, Guangzhou Li, Bo Ma, Meng Liu, Shuaishuai Chi, Qingxi Beijing Electro-Mechanical Engineering Institute Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Coopration Laboratory Beijing China

ISBN: (纸本)9781665498142

Focused on revising the cumulative error of the SINS, a dual-mode navigation algorithm based on the infrared and SAR information fusion is studied in this paper. The SAR system can provide the SAR image and the information including the distance and the beam direction of the SAR antenna, the infrared system can provide the infrared image and the optical axis direction of the infrared lens. Under the premise of the same direction of the SAR and infrared beam, a navigation algorithm by associating the matching results of the SAR image and infrared image with the digital map is studied, which can be applied to amend the aberration of the SINS in the middle phase. At the same time, the common aperture characteristic and GPS error isolation method are used to isolate the error sub area. The simulation results reveal the validity of the algorithm. © 2021 IEEE.

关键词： fusion infrared information navigation SAR information

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Distance estimation of obstacles in monocular vision based on deep learning 8

Distance estimation of obstacles in monocular vision based o...

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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Shan, Liu Ming, Li Long Hui, Wei Dong Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China China Aerospace Science and Industry Corporation Limited Beijing100048 China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

Aiming at the forward-looking distance perception requirements of obstacles such as mountains, forests and trees during the ultra-low-altitude flight of subsonic aircraft, an obstacle distance estimation method based on deep learning is proposed. Firstly, the relationship between adjacent hyper-pixels is modeled by the conditional random fields, the neural network model is trained using the data set, and then the loss function of the pose parameter regression is designed, and the representation of the neural network model is input to the constructed loss function to optimize the weight of the regression model. Simulation experiments show that the proposed method can effectively perceive obstacles within 3km ahead, and the distance estimation error is not more than 20% of the relative distance, which can meet the obstacle avoidance requirements of most sudden obstacles during ultra-low-altitude flight. © 2022 SPIE

关键词： Vision

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A Noise Filter for Dynamic Vision Sensor Based on Spatiotemporal Correlation and Hot Pixel Detection

A Noise Filter for Dynamic Vision Sensor Based on Spatiotemp...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Xu, Ninghui Zhao, Jiajia Ren, Yuan Wang, Lihui Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811694912

As a new type of neuromorphic sensor, the events-driven Dynamic Vision Sensor (DVS) has the advantages of low latency and wide dynamic range. The development of DVS overcomes the application limitations of traditional cameras in the field of high speed robots and autonomous driving. However, there are abundant unwanted noise events contained in the output of DVS, which severely affects the subsequent data-processing. To tackle the problem, a novel noise filter for DVS is proposed in this paper. Firstly, since the noise is composed of hot pixel events with high-frequency and random background activities, a time window is constructed to continuously detect hot pixels. Secondly, a spatiotemporal correlation-based denoising approach for each incoming event is conducted, while excluding its surrounding hot pixels, to avoid the negative effect caused by their high temporal correlation on the filter. Finally, the hot pixels are compensated with the events that are most probably to occur depending on the adjacent events, to achieve the completeness and precision of the output event stream. Experiments in different scenes demonstrate that the proposed noise filter can effectively eliminate the noise from the event stream of DVS and obviously outperforms the baseline method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pixels

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Cross-Domain Guidance Positioning Method Based on Multi-Layer Network Structure 21

Cross-Domain Guidance Positioning Method Based on Multi-Laye...

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3rd European Symposium on Computer and Communications, ESCC 2021

作者： Wu, ChengFeng Guo, XiaoYun Xu, Cheng Qi, Hang Liu, Yanxu Zhao, Jianmin Hu, Enwen Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory China Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781450387491

Oriented towards the requirements for reliable positioning and navigation of aircraft under the condition of rejection of navigation satellite, we proposed cross-domain guide positioning methods based on multi-layer network coverage, and designed the relative positioning network construction methods between ground nodes, aircrafts and ground nodes, aircrafts and target nodes. Combined with the relative positioning network characteristics of each layer, at the same time, considered the computational complexity and location accuracy, the self-established multi-point coordinate system method and the robust location method are proposed. © 2021 ACM.

关键词： Aircraft

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The design of a displaying system for battlefield situation based on ArcGIS Engine

The design of a displaying system for battlefield situation ...

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2021 China Automation Congress, CAC 2021

作者： Wang, Jiaqi Xu, Cheng Ji, Hua Science and Technology on Complex System Control and Ietelligent Agent Coopration Laboratory Beijing10074 China Beijing Electro-Mechanical Engineering Institute Beijing10074 China

ISBN: (纸本)9781665426473

To facilitate the precise analysis and judgment of battlefield situation for military stuffs inmodern warfare with abundant information, a modularized two-dimension battlefield situation displaysystem is designed based on ArcGIS Engine in this paper. The functions of each module are analyzed, andkey issues of the design are introduced. The real-time dynamic display of moving objects in the battlefield isachieved by reading data from the battlefield. © 2021 IEEE

关键词： Engines

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